Low-Complexity Lossless Compression of Hyperspectral Imagery via Adaptive Filtering

Onboard compression of hyperspectral imagery is important for reducing the burden on downlink resources. Here we describe a novel adaptive predictive technique for lossless compression of hyperspectral data. This technique uses an adaptive filtering method and achieves a combination of low complexity and compression effectiveness that is competitive with the best results from the literature. Although we are primarily interested in application to hyperspectral imagery, the technique is also generally applicable to any sort of multispectral imagery.